Ziyuan Li

Ph.D. Candidate

Marketing

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Education

Ph.D. in Business, Marketing concentration, University of Connecticut, 2027 (expected)
Masters in Marketing Science, Columbia University, 2021
B.S. in Management Information System, Beijing Jiaotong University (China), 2020

 

Research Interest

Substantive: Digital platforms, User-generated content, media & entertainment (streaming, video games), tourism & hospitality

Methodological: Causal inference (e.g., difference-in-differences), Machine Learning (e.g., transformers, LLM prompting), Field experiments

 

Biography

Ziyuan Li is a fourth-year PhD candidate in Marketing at the University of Connecticut. Her research leverages machine learning, Large Language Models (LLMs), and causal inference to understand consumer dynamics on digital platforms. In particular, she uses transformer-based models with LLM prompting to improve interpretability and enhance marketers’ ability to make data-driven decisions. Using large-scale platform data and field experiments, she studies how platform design shapes engagement and demand.

 

Honors and Awards

2025 ISMS Doctoral Dissertation Early-Stage Research Grant — Selected as one of only four winners, receiving a $4,000 grant for outstanding research in Marketing Science
Selected to attend the 2025 Marketing Science Consortium
Selected to attend the 2026 Marketing Science Consortium
Invited to the 2026 AMA-Sheth Foundation Doctoral Consortium
Summer Fellowship, University of Connecticut (Summer 2023, Summer 2024, Summer 2025)

 

Research Experience

Research Assistant, University of Connecticut
  Dr. Joseph Pancras, Fall 2022, Spring 2024, Spring 2025

  Dr. Jane Gu, Spring 2023, Fall 2024, Fall 2026

  Dr. Vishal Narayan, Fall 2023
Dr. Weining Bao, Spring 2026

Behavior Lab Assistant, University of Connecticut, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Fall 2026

 

Teaching Experience

Instructor, University of Connecticut
Introduction to Marketing Management (MKTG 3101), Spring 2025, Spring 2026

Teaching Assistant, University of Connecticut
  Marketing and Digital Analytics, Fall 2022, Fall 2023, Spring 2024, Fall 2024, Fall 2026

  Marketing Planning and Strategy, Spring 2023